Publications by authors named "Dharmadi"

The deep ocean is the last natural biodiversity refuge from the reach of human activities. Deepwater sharks and rays are among the most sensitive marine vertebrates to overexploitation. One-third of threatened deepwater sharks are targeted, and half the species targeted for the international liver-oil trade are threatened with extinction.

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Sharks and rays are key functional components of coral reef ecosystems, yet many populations of a few species exhibit signs of depletion and local extinctions. The question is whether these declines forewarn of a global extinction crisis. We use IUCN Red List to quantify the status, trajectory, and threats to all coral reef sharks and rays worldwide.

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The proposed architecture applies the principle of predictive coding and deep learning in a brain-inspired approach to robotic sensorimotor control. It is composed of many layers each of which is a recurrent network. The component networks can be spontaneously active due to the homeokinetic learning rule, a principle that has been studied previously for the purpose of self-organized generation of behavior.

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Indonesia has the greatest reported chondrichthyan catches worldwide, with c.110,000 t caught annually. The pelagic thresher (Alopias pelagicus) and scalloped hammerhead (Sphryna lewini) together comprise about 25% of the total catches of sharks landed in Indonesia.

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The biological aspects of members of the order Orectolobiformes exploited in Indonesian waters are given. Seven species belonging to five families were recorded in the catches at various landing sites in southern Indonesia. Of these, Chiloscyllium punctatum was the most abundant species landed, contributing >50% of the number of orectolobiforms recorded.

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The complex multi-gear, multi-species tropical fisheries in developing countries are poorly understood and characterising the landings from these fisheries is often impossible using conventional approaches. A rapid assessment method for characterising landings at fish markets, using an index of abundance and estimated weight within taxonomic groups, is described. This approach was developed for contexts where there are no detailed data collection protocols, and where consistent data collection across a wide range of fisheries types and geographic areas is required, regardless of the size of the site and scale of the landings.

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DNA 'assembly' from 'building blocks' remains a cornerstone in synthetic biology, whether it be for gene synthesis (∼ 1 kb), pathway engineering (∼ 10 kb) or synthetic genomes (>100 kb). Despite numerous advances in the techniques used for DNA assembly, verification of the assembly is still a necessity, which becomes cost-prohibitive and a logistical challenge with increasing scale. Here we describe for the first time a comprehensive, high-throughput solution for structural DNA assembly verification by restriction digest using exhaustive in silico enzyme screening, rolling circle amplification of plasmid DNA, capillary electrophoresis and automated digest pattern recognition.

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Biological data were recorded for 1265 silky sharks Carcharhinus falciformis collected from fish landing sites in eastern Indonesia. These represented catches taken in most calendar months by gillnetting and longlining in the eastern Indian Ocean and contained individuals ranging from embryos to fully mature adults. The growth zones in centra, which were shown to form annually, were counted in the vertebrae in a sub-sample of 200 fish for ageing purposes.

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Three species of hexanchiform sharks belonging to two families and 12 species of squaliform sharks belonging to three families were recorded in fish landing site surveys in eastern Indonesia. Of these, the Squalidae were the most abundant species landed, with Squalus hemipinnis, Squalus edmundsi and Squalus montalbani contributing 0.4, 0.

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Complexity of regulatory networks arises from the high degree of interaction between network components such as DNA, RNA, proteins, and metabolites. We have developed a modeling tool, elementary network reconstruction (ENR), to characterize these networks. ENR is a knowledge-driven, steady state, deterministic, quantitative modeling approach based on linear perturbation theory.

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Anaerobic fermentation of glycerol in the Enterobacteriaceae family has long been considered a unique property of species that synthesize 1,3-propanediol (1,3-PDO). However, we have discovered that Escherichia coli can ferment glycerol in a 1,3-PDO-independent manner. We identified 1,2-propanediol (1,2-PDO) as a fermentation product and established the pathway that mediates its synthesis as well as its role in the metabolism of glycerol.

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Availability, low prices, and a high degree of reduction make glycerol an ideal feedstock to produce reduced chemicals and fuels via anaerobic fermentation. Although glycerol metabolism in Escherichia coli had been thought to be restricted to respiratory conditions, we report here the utilization of this carbon source in the absence of electron acceptors. Cells grew fermentatively on glycerol and exhibited exponential growth at a maximum specific growth rate of 0.

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The worldwide surplus of glycerol generated as inevitable byproduct of biodiesel fuel and oleochemical production is resulting in the shutdown of traditional glycerol-producing/refining plants and new applications are needed for this now abundant carbon source. In this article we report our finding that Escherichia coli can ferment glycerol in a pH-dependent manner. We hypothesize that glycerol fermentation is linked to the availability of CO(2), which under acidic conditions is produced by the oxidation of formate by the enzyme formate hydrogen lyase (FHL).

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HPLC optimization strategy consists of four elements; experimental design, retention modeling, quality criteria function, and optimum search method. In this paper we present a simple, superior alternative to general classes of classical resolution functions (S function) and a novel optimum search algorithm (iterative stochastic search, ISS) for HPLC optimization. Comparison of S with general classes of resolution-based quality criteria functions (Rs, Rp, and Rmin) shows superior features such as correct assessment of favorable separation conditions, preservation of peak pair contributions, elimination of arbitrary cut-off values, and a unique capability to interpret absolute significance of function values through a simple inequality.

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DNA microarrays are currently used to study the transcriptional response of many organisms to genetic and environmental perturbations. Although there is much room for improvement of this technology, its potential has been clearly demonstrated in the past 5 years. The general consensus is that the bottleneck is now located in the processing and analysis of transcriptome data and its use for purposes other than the quantification of changes in gene expression levels.

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